Timezone: »
As the application of deep learning has expanded to real-world problems with insufficient volume of training data, transfer learning recently has gained much attention as means of improving the performance in such small-data regime. However, when existing methods are applied between heterogeneous architectures and tasks, it becomes more important to manage their detailed configurations and often requires exhaustive tuning on them for the desired performance. To address the issue, we propose a novel transfer learning approach based on meta-learning that can automatically learn what knowledge to transfer from the source network to where in the target network. Given source and target networks, we propose an efficient training scheme to learn meta-networks that decide (a) which pairs of layers between the source and target networks should be matched for knowledge transfer and (b) which features and how much knowledge from each feature should be transferred. We validate our meta-transfer approach against recent transfer learning methods on various datasets and network architectures, on which our automated scheme significantly outperforms the prior baselines that find “what and where to transfer” in a hand-crafted manner.
Author Information
Yunhun Jang (OMNIOUS)
Hankook Lee (KAIST)
Sung Ju Hwang (KAIST, AITRICS)
Jinwoo Shin (KAIST, AITRICS)
Related Events (a corresponding poster, oral, or spotlight)
-
2019 Poster: Learning What and Where to Transfer »
Fri. Jun 14th 01:30 -- 04:00 AM Room Pacific Ballroom #186
More from the Same Authors
-
2021 : SmoothMix: Training Confidence-calibrated Smoothed Classifiers for Certified Adversarial Robustness »
Jongheon Jeong · Sejun Park · Minkyu Kim · Heung-Chang Lee · Doguk Kim · Jinwoo Shin -
2021 : Entropy Weighted Adversarial Training »
Minseon Kim · Jihoon Tack · Jinwoo Shin · Sung Ju Hwang -
2021 : Consistency Regularization for Adversarial Robustness »
Jihoon Tack · Sihyun Yu · Jongheon Jeong · Minseon Kim · Sung Ju Hwang · Jinwoo Shin -
2023 Poster: Prefer to Classify: Improving Text Classifiers via Auxiliary Preference Learning »
Jaehyung Kim · Jinwoo Shin · Dongyeop Kang -
2023 Poster: Modality-Agnostic Variational Compression of Implicit Neural Representations »
Jonathan Richard Schwarz · Jihoon Tack · Yee-Whye Teh · Jaeho Lee · Jinwoo Shin -
2023 Poster: Multi-View Masked World Models for Visual Robotic Manipulation »
Younggyo Seo · Junsu Kim · Stephen James · Kimin Lee · Jinwoo Shin · Pieter Abbeel -
2022 Poster: TSPipe: Learn from Teacher Faster with Pipelines »
Hwijoon Lim · Yechan Kim · Sukmin Yun · Jinwoo Shin · Dongsu Han -
2022 Poster: Score-based Generative Modeling of Graphs via the System of Stochastic Differential Equations »
Jaehyeong Jo · Seul Lee · Sung Ju Hwang -
2022 Spotlight: Score-based Generative Modeling of Graphs via the System of Stochastic Differential Equations »
Jaehyeong Jo · Seul Lee · Sung Ju Hwang -
2022 Spotlight: TSPipe: Learn from Teacher Faster with Pipelines »
Hwijoon Lim · Yechan Kim · Sukmin Yun · Jinwoo Shin · Dongsu Han -
2022 Poster: Disentangling Sources of Risk for Distributional Multi-Agent Reinforcement Learning »
Kyunghwan Son · Junsu Kim · Sungsoo Ahn · Roben Delos Reyes · Yung Yi · Jinwoo Shin -
2022 Poster: Forget-free Continual Learning with Winning Subnetworks »
Haeyong Kang · Rusty Mina · Sultan Rizky Hikmawan Madjid · Jaehong Yoon · Mark Hasegawa-Johnson · Sung Ju Hwang · Chang Yoo -
2022 Poster: Set Based Stochastic Subsampling »
Bruno Andreis · Seanie Lee · A. Tuan Nguyen · Juho Lee · Eunho Yang · Sung Ju Hwang -
2022 Poster: Time Is MattEr: Temporal Self-supervision for Video Transformers »
Sukmin Yun · Jaehyung Kim · Dongyoon Han · Hwanjun Song · Jung-Woo Ha · Jinwoo Shin -
2022 Poster: Bitwidth Heterogeneous Federated Learning with Progressive Weight Dequantization »
Jaehong Yoon · Geon Park · Wonyong Jeong · Sung Ju Hwang -
2022 Spotlight: Forget-free Continual Learning with Winning Subnetworks »
Haeyong Kang · Rusty Mina · Sultan Rizky Hikmawan Madjid · Jaehong Yoon · Mark Hasegawa-Johnson · Sung Ju Hwang · Chang Yoo -
2022 Spotlight: Disentangling Sources of Risk for Distributional Multi-Agent Reinforcement Learning »
Kyunghwan Son · Junsu Kim · Sungsoo Ahn · Roben Delos Reyes · Yung Yi · Jinwoo Shin -
2022 Spotlight: Time Is MattEr: Temporal Self-supervision for Video Transformers »
Sukmin Yun · Jaehyung Kim · Dongyoon Han · Hwanjun Song · Jung-Woo Ha · Jinwoo Shin -
2022 Spotlight: Bitwidth Heterogeneous Federated Learning with Progressive Weight Dequantization »
Jaehong Yoon · Geon Park · Wonyong Jeong · Sung Ju Hwang -
2022 Spotlight: Set Based Stochastic Subsampling »
Bruno Andreis · Seanie Lee · A. Tuan Nguyen · Juho Lee · Eunho Yang · Sung Ju Hwang -
2021 : Contrastive Learning for Novelty Detection »
Jinwoo Shin -
2021 Poster: Large-Scale Meta-Learning with Continual Trajectory Shifting »
JaeWoong Shin · Hae Beom Lee · Boqing Gong · Sung Ju Hwang -
2021 Poster: Self-Improved Retrosynthetic Planning »
Junsu Kim · Sungsoo Ahn · Hankook Lee · Jinwoo Shin -
2021 Spotlight: Self-Improved Retrosynthetic Planning »
Junsu Kim · Sungsoo Ahn · Hankook Lee · Jinwoo Shin -
2021 Spotlight: Large-Scale Meta-Learning with Continual Trajectory Shifting »
JaeWoong Shin · Hae Beom Lee · Boqing Gong · Sung Ju Hwang -
2021 Poster: Learning to Generate Noise for Multi-Attack Robustness »
Divyam Madaan · Jinwoo Shin · Sung Ju Hwang -
2021 Poster: Adversarial Purification with Score-based Generative Models »
Jongmin Yoon · Sung Ju Hwang · Juho Lee -
2021 Spotlight: Adversarial Purification with Score-based Generative Models »
Jongmin Yoon · Sung Ju Hwang · Juho Lee -
2021 Spotlight: Learning to Generate Noise for Multi-Attack Robustness »
Divyam Madaan · Jinwoo Shin · Sung Ju Hwang -
2021 Poster: Meta-StyleSpeech : Multi-Speaker Adaptive Text-to-Speech Generation »
Dongchan Min · Dong Bok Lee · Eunho Yang · Sung Ju Hwang -
2021 Spotlight: Meta-StyleSpeech : Multi-Speaker Adaptive Text-to-Speech Generation »
Dongchan Min · Dong Bok Lee · Eunho Yang · Sung Ju Hwang -
2021 Poster: Federated Continual Learning with Weighted Inter-client Transfer »
Jaehong Yoon · Wonyong Jeong · GiWoong Lee · Eunho Yang · Sung Ju Hwang -
2021 Poster: State Entropy Maximization with Random Encoders for Efficient Exploration »
Younggyo Seo · Lili Chen · Jinwoo Shin · Honglak Lee · Pieter Abbeel · Kimin Lee -
2021 Spotlight: Federated Continual Learning with Weighted Inter-client Transfer »
Jaehong Yoon · Wonyong Jeong · GiWoong Lee · Eunho Yang · Sung Ju Hwang -
2021 Spotlight: State Entropy Maximization with Random Encoders for Efficient Exploration »
Younggyo Seo · Lili Chen · Jinwoo Shin · Honglak Lee · Pieter Abbeel · Kimin Lee -
2020 Poster: Cost-Effective Interactive Attention Learning with Neural Attention Processes »
Jay Heo · Junhyeon Park · Hyewon Jeong · Kwang Joon Kim · Juho Lee · Eunho Yang · Sung Ju Hwang -
2020 Poster: Meta Variance Transfer: Learning to Augment from the Others »
Seong-Jin Park · Seungju Han · Ji-won Baek · Insoo Kim · Juhwan Song · Hae Beom Lee · Jae-Joon Han · Sung Ju Hwang -
2020 Poster: Self-supervised Label Augmentation via Input Transformations »
Hankook Lee · Sung Ju Hwang · Jinwoo Shin -
2020 Poster: Context-aware Dynamics Model for Generalization in Model-Based Reinforcement Learning »
Kimin Lee · Younggyo Seo · Seunghyun Lee · Honglak Lee · Jinwoo Shin -
2020 Poster: Polynomial Tensor Sketch for Element-wise Function of Low-Rank Matrix »
Insu Han · Haim Avron · Jinwoo Shin -
2020 Poster: Learning What to Defer for Maximum Independent Sets »
Sungsoo Ahn · Younggyo Seo · Jinwoo Shin -
2020 Poster: Adversarial Neural Pruning with Latent Vulnerability Suppression »
Divyam Madaan · Jinwoo Shin · Sung Ju Hwang -
2019 Poster: Spectral Approximate Inference »
Sejun Park · Eunho Yang · Se-Young Yun · Jinwoo Shin -
2019 Poster: Robust Inference via Generative Classifiers for Handling Noisy Labels »
Kimin Lee · Sukmin Yun · Kibok Lee · Honglak Lee · Bo Li · Jinwoo Shin -
2019 Oral: Spectral Approximate Inference »
Sejun Park · Eunho Yang · Se-Young Yun · Jinwoo Shin -
2019 Oral: Robust Inference via Generative Classifiers for Handling Noisy Labels »
Kimin Lee · Sukmin Yun · Kibok Lee · Honglak Lee · Bo Li · Jinwoo Shin -
2019 Poster: Training CNNs with Selective Allocation of Channels »
Jongheon Jeong · Jinwoo Shin -
2019 Oral: Training CNNs with Selective Allocation of Channels »
Jongheon Jeong · Jinwoo Shin -
2018 Poster: Deep Asymmetric Multi-task Feature Learning »
Hae Beom Lee · Eunho Yang · Sung Ju Hwang -
2018 Poster: Bucket Renormalization for Approximate Inference »
Sungsoo Ahn · Michael Chertkov · Adrian Weller · Jinwoo Shin -
2018 Oral: Deep Asymmetric Multi-task Feature Learning »
Hae Beom Lee · Eunho Yang · Sung Ju Hwang -
2018 Oral: Bucket Renormalization for Approximate Inference »
Sungsoo Ahn · Michael Chertkov · Adrian Weller · Jinwoo Shin -
2017 Poster: Faster Greedy MAP Inference for Determinantal Point Processes »
Insu Han · Prabhanjan Kambadur · Kyoungsoo Park · Jinwoo Shin -
2017 Poster: Confident Multiple Choice Learning »
Kimin Lee · Changho Hwang · KyoungSoo Park · Jinwoo Shin -
2017 Talk: Confident Multiple Choice Learning »
Kimin Lee · Changho Hwang · KyoungSoo Park · Jinwoo Shin -
2017 Talk: Faster Greedy MAP Inference for Determinantal Point Processes »
Insu Han · Prabhanjan Kambadur · Kyoungsoo Park · Jinwoo Shin